1. Simulation of an MPGD application for Homeland Security Muon Tomography for detection of Nuclear contraband Kondo Gnanvo, M. Hohlmann, P. Ford, J. Helsby, R. Hoch, D. Mitra Florida Institute of Technology

2. Outline • MPGD for Muon Tomography • Simulation of Muon Tomography Station performances • Results and limitations • Plans for the future

3. Muon Tomography to prevent nuclear material contraband • Highly Enriched Uranium (HEU) or highly radioactive material could be smuggled across border for terrorist attack • Various detection techniques in place or understudy to prevent smuggling and contraband of such dangerous materials across borders • Muon Tomography based on cosmic ray muons is one promising detection technique

4. Muon Tomography Station (MTS) based on cosmic ray muons Q=+92e μ • Multiple Coulomb scattering is ~ prop. to Z and could discriminate materials by Z • Cosmic ray muons: natural radiation source or no beam needed • Muons highly penetrating; potential for sensing high-Z material shielded by Fe or Pb μ Cargo container Q=+26e Θ 235U Θ 92 hidden & shielded high-Z nuclear material 56Fe HEU: Big scattering angles! μ Θ 26 Θ Regular material: small scattering angles Tracking Detector μ tracks Gas Electron Multipliers (GEMs) as tracking detectors for the MTS • Advantages: • Excellent 2D spatial resolution =>precise scattering angle measurement • Thin detectors layer => low material => low scattering with the detectors • Compact • Challenges: • Building large size detectors • Maintaining the excellent resolution for large size detectors • Cost of the readout and electronics F. Sauli

5. Simulation of the performances of Muon Tomography Station • We use CRY to generate the cosmic ray muons • cosmic ray package developped at Laurence Livermore NL • Package interfaced with GEANT4 • We use GEANT4 for the simulation • Physics of muons interaction with matter • Tracking of the muons with their recorded position measurement by the GEM detectors • ROOT and AIDA/JAS for analysis and plotting of the results

6. Simulation of the performances of Muon Tomography Station • G4 simulation Geometry for the MTS: • 3 Detectors per planes (top, bottom laterals)‏ • From 1 to up to 10 targets of different materials from low Z Al to high Z U • CRY for cosmic muons as primary particles • We collect the incoming and outgoing muon position recorded at the detectors level • Reconstruction of the muons track • Point Of Closest Approach (POCA) algorithm is used to get the interaction point of each muon • The scattering angle of the muon calculated • The MTS volume is divided in voxels (10 cm); each voxel displays the mean scattering angle of all the POCA points it contains. The value of the angle is then a good approximation of the z value of the material

7. Acceptance and coverage of the MTS Side View (x-z plane) Top View (x-y plane) MT station type ~ 10 min exposure => ~ 2500 muons in maximum coverage voxel. Top & bottom detectors only z 3m 3% of the volume around the center with 80% of voxel with max muons y x Top, bottom & side detectors Maximum coverage 10% higher 18% of the volume around the center with 80% of voxel with max muons z y x

8. Scattering Angle Distribution With resolution, the reconstructed POCA point of small deviation angle muons don’t fall within the material volume. • The reconstructed mean value of the scattering angle is then higher the than the actual mean angle for the given material. • The POCA points are scattered all around the MTS volume. The statistic is then smaller in the volume defined by the material. Uranium

9. Reconstructed targets Perfect resolution The higher Z value is, the more accurate the POCA reconstruction

10. Systematic effect on the mean angle Effect of the position of the targets in the MTS volume: Uranium Effect of the target dimensions

11. Systematic effects on the mean angle Effect of the detectors resolution Effect of the gap between the detectors

12. U W Pb U W U W Pb Pb Significance of Excess and U hypothesis test: 10 min Exposure @ 99% confidence Excess above Fe background U hypothesis Sig Sig W U W U U W Pb > 5σ in ALL high-Z voxels Pb Pb Sig Sig W W U U Pb Pb

13. Significance of Excess and U hypothesis test: 1 min exposure @ 99% confidence Excess above Fe background U hypothesis W U U W W U U W Pb Pb Pb Pb W W U U W W U U Pb Pb Pb Pb

14. Advanced reconstruction: Expectation Maximisation Algorithm (EM) • Reproducing Los Alamos Expectation Max. algorithm (L. Schultz et al.)‏ • Input: Use lateral shift Δxi in multiple scattering as additional information on top of scattering angle θi for each (i-th) muon track • Output:Scattering density λkfor each (k-th) voxel of the volume • λ relates the variance of scattering with radiation length (or Z value) of the respective material • Procedure: Maximize log-likelihood for assignment of scattering densities to all independent voxels given observed  tracks • Analytical derivation leads to an iterative formula for incrementally updating λk values in each iteration

15. Plans for the next months • Start the building a our first GEM detector: • Working on a with 10 cm x 10 cm foils prototype. • Readout and electronics development. • Expect our first MTS prototype some time next year. • Continue simulation work: • Improvement the EM algorithm for the reconstruction. • Get involve MPGD detector simulation (GEANT4, Garfield integration).

16. Conclusion • We report advanced simulation results of MuonTomography detection technique. • Large size and excellent spatial resolution tracking detectors are needed for the MTS. • We proposed to use large size GEM detectors. • Big challenges ahead in terms of statistics (low rate cosmic muons) and resolution. • Plan to switch from simulation to building a MTS prototype • Get a small size GEM detectors working. • Build a medium size MTS prototype and compared with simulation. • Still some simulation and algorithm development needed. • Our group is new in MPGDs so we need all expertise from you to meet our challenges of building a MTS with large size MPGDs.